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Update app.py
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app.py
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@@ -5,7 +5,10 @@ import duckdb
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import openai
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# 1) Load your OpenAI key from the Space’s Secrets
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# 2) Load your synthetic data into DuckDB
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df = pd.read_csv('synthetic_profit.csv')
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@@ -22,18 +25,22 @@ def generate_sql(question: str) -> str:
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f"with columns: {schema}. "
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"Translate the user's question into a valid SQL query and return ONLY the SQL."
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sql = resp.choices[0].message.content.strip()
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# strip
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if sql.startswith("```") and sql.endswith("```"):
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sql = "\n".join(sql.splitlines()[1:-1])
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return sql
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@@ -41,25 +48,32 @@ def generate_sql(question: str) -> str:
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# 5) Core Q&A function: NL → SQL → execute → format
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def answer_profitability(question: str) -> str:
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# a) turn the question into SQL
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# b) try to run it
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try:
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result_df = conn.execute(sql).df()
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except Exception as e:
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return (
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f"❌
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f"Generated SQL
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)
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# c) format the result
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if result_df.empty:
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return f"No rows returned.\n\n```sql\n{sql}\n```"
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# single-cell → scalar
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if result_df.shape == (1,1):
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return str(result_df.iat[0,0])
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return result_df.to_markdown(index=False)
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# 6) Gradio interface with explicit outputs
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iface = gr.Interface(
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fn=answer_profitability,
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inputs=gr.Textbox(lines=2, placeholder="Ask a question about profitability…", label="Question"),
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import openai
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# 1) Load your OpenAI key from the Space’s Secrets
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OPENAI_KEY = os.getenv("OPENAI_API_KEY")
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if not OPENAI_KEY:
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raise RuntimeError("Missing OPENAI_API_KEY secret in your Space settings")
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openai.api_key = OPENAI_KEY
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# 2) Load your synthetic data into DuckDB
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df = pd.read_csv('synthetic_profit.csv')
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f"with columns: {schema}. "
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"Translate the user's question into a valid SQL query and return ONLY the SQL."
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)
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try:
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resp = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": question},
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],
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temperature=0.0,
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max_tokens=150,
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)
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except Exception as e:
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# Catch network/auth errors
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raise RuntimeError(f"OpenAI API error: {e}")
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sql = resp.choices[0].message.content.strip()
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# strip triple-backticks if present
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if sql.startswith("```") and sql.endswith("```"):
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sql = "\n".join(sql.splitlines()[1:-1])
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return sql
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# 5) Core Q&A function: NL → SQL → execute → format
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def answer_profitability(question: str) -> str:
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# a) turn the question into SQL
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try:
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sql = generate_sql(question)
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except Exception as e:
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return f"❌ **OpenAI Error**\n{e}"
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# b) try to run it
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try:
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result_df = conn.execute(sql).df()
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except Exception as e:
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return (
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f"❌ **SQL Execution Error**\n{e}\n\n"
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f"**Generated SQL**\n```sql\n{sql}\n```"
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)
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# c) format the result
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if result_df.empty:
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return f"No rows returned.\n\n```sql\n{sql}\n```"
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# single-cell → scalar
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if result_df.shape == (1,1):
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return str(result_df.iat[0,0])
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# multi-cell → markdown table
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return result_df.to_markdown(index=False)
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# 6) Gradio interface with explicit inputs & outputs
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iface = gr.Interface(
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fn=answer_profitability,
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inputs=gr.Textbox(lines=2, placeholder="Ask a question about profitability…", label="Question"),
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